---
library_name: transformers
license: apache-2.0
base_model: facebook/wav2vec2-base
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: w2v2-base_kabir
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# w2v2-base_kabir

This model is a fine-tuned version of [facebook/wav2vec2-base](https://huggingface.co/facebook/wav2vec2-base) on the [Medical Speech, Transcription, and Intent](https://www.kaggle.com/datasets/paultimothymooney/medical-speech-transcription-and-intent) dataset.
It achieves the following results on the evaluation set:
- Loss: 0.9705
- Wer: 0.3289

## Model description

More information needed

## Intended uses & limitations

More information needed

## Training and evaluation data

More information needed

## Training procedure

### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 5e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 250
- training_steps: 2500
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch    | Step | Validation Loss | Wer    |
|:-------------:|:--------:|:----:|:---------------:|:------:|
| 2.8771        | 20.8333  | 500  | 2.8897          | 1.0    |
| 0.3115        | 41.6667  | 1000 | 0.9687          | 0.4125 |
| 0.1248        | 62.5     | 1500 | 0.9421          | 0.3502 |
| 0.0658        | 83.3333  | 2000 | 0.9894          | 0.3348 |
| 0.0703        | 104.1667 | 2500 | 0.9705          | 0.3289 |


### Framework versions

- Transformers 4.45.1
- Pytorch 2.4.0
- Datasets 3.0.1
- Tokenizers 0.20.0